Aiming to strengthen classical secret-sharing to make it a more directly useful primitive for human endusers, we develop definitions, theorems, and efficient constructions for what we call adept secret-sharing. Our primary concerns are the properties we call privacy, authenticity, and error correction. Privacy strengthens the classical requirement by ensuring maximal confidentiality even if the dealer does not employ fresh, uniformly random coins with each sharing. That might happen either intentionally—to enable reproducible secretsharing— or unintentionally, when an entropy source fails. Authenticity is a shareholder’s guarantee that a secret recovered using his or her share will coincide with the value the dealer committed to at the time the secret was shared. Error correction is the guarantee that recovery of a secret will succeed, also identifying the valid shares, exactly when there is a unique explanation as to which shares implicate what secret. These concerns arise organically from a desire to create general-purpose libraries and apps for secret sharing that can withstand both strong adversaries and routine operational errors.

Towards advancing the use of big keys as a practical defense against key exfiltration, this paper provides efficiency improvements for cryptographic schemes in the bounded retrieval model (BRM). We identify probe complexity (the number of scheme accesses to the slow storage medium storing the big key) as the dominant cost. Our main technical contribution is what we call the large-alphabet subkey prediction lemma. It gives good bounds on the predictability under leakage of a random sequence of blocks of the big key, as a function of the block size. We use it to significantly reduce the probe complexity required to attain a given level of security. Together with other techniques, this yields security-preserving performance improvements for BRM symmetric encryption schemes and BRM public-key identification schemes.